A production-grade Model Context Protocol (MCP) server. Empowers AI assistants (Claude, Cursor) to search, fetch, and analyze Reddit discussions with resilient rate-limiting and smart LLM noise filter
A highly resilient, open-source Model Context Protocol (MCP) server. It empowers AI models (such as Claude and Cursor) to search, fetch, read, and deep-dive into Reddit content with robust rate-limiting recovery and smart comment-filtering.
Built in Python using FastMCP, this project adheres to a strict 4-Layer Architecture designed for high modularity, testability, and painless contributions.
Here is a visual sequence diagram showing how the AI model interacts with this server, including our Zero-Config Fallback system:
- 🚀 Zero-Config Ready: Works completely out of the box! No Reddit API keys required. If credentials are not provided, it seamlessly falls back to DuckDuckGo and the Arctic Shift archive. - 🛡️ Graceful Degradation: Intelligently switches between the official Reddit API and unauthenticated fallback providers without crashing, ensuring the LLM always gets data. - 📈 Resilient HTTP Client: Built-in exponential backoff and rate-limiting recovery. If Reddit says 429 Too Many Requests, the server respects the Retry-After header and retries automatically. - 🔍 Strategic Search: Integrates a decoupled search provider system (Strategy Pattern) allowing easy addition of custom search engines. - 🤖 LLM-Safe Filtering: Cleans thread payloads by dropping auto-moderators, bot notifications, and low-quality comments, saving precious LLM token costs. - ⏱️ Strict LLM Timeout Protection: Uses decorators to force safe API timeouts, returning clean graceful JSON-RPC fallbacks instead of hanging the AI client.
From the project README.
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